scholarly journals Species and Phenotypic Distribution Models Reveal Population Differentiation in Ethiopian Indigenous Chickens

2021 ◽  
Vol 12 ◽  
Author(s):  
Fasil Getachew Kebede ◽  
Hans Komen ◽  
Tadelle Dessie ◽  
Setegn Worku Alemu ◽  
Olivier Hanotte ◽  
...  
Keyword(s):  
Habitat Suitability ◽  
Environmental Variables ◽  
Quantitative Traits ◽  
Poultry Production ◽  
Distribution Models ◽  
Phenotypic Differentiation ◽  
Selective Pressures ◽  
Phenotypic Distribution ◽  
Indigenous Chickens ◽  
The Relationship

Smallholder poultry production dominated by indigenous chickens is an important source of livelihoods for most rural households in Ethiopia. The long history of domestication and the presence of diverse agroecologies in Ethiopia create unique opportunities to study the effect of environmental selective pressures. Species distribution models (SDMs) and Phenotypic distribution models (PDMs) can be applied to investigate the relationship between environmental variation and phenotypic differentiation in wild animals and domestic populations. In the present study we used SDMs and PDMs to detect environmental variables related with habitat suitability and phenotypic differentiation among nondescript Ethiopian indigenous chicken populations. 34 environmental variables (climatic, soil, and vegetation) and 19 quantitative traits were analyzed for 513 adult chickens from 26 populations. To have high variation in the dataset for phenotypic and ecological parameters, animals were sampled from four spatial gradients (each represented by six to seven populations), located in different climatic zones and geographies. Three different ecotypes are proposed based on correlation test between habitat suitability maps and phenotypic clustering of sample populations. These specific ecotypes show phenotypic differentiation, likely in response to environmental selective pressures. Nine environmental variables with the highest contribution to habitat suitability are identified. The relationship between quantitative traits and a few of the environmental variables associated with habitat suitability is non-linear. Our results highlight the benefits of integrating species and phenotypic distribution modeling approaches in characterization of livestock populations, delineation of suitable habitats for specific breeds, and understanding of the relationship between ecological variables and quantitative traits, and underlying evolutionary processes.

scholarly journals Mapping current and potential future distributions of the oak tree (Quercus aegilops) in the Kurdistan Region, Iraq

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Nabaz R. Khwarahm
Keyword(s):  
Climate Change ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Climate Changes ◽  
Future Climate ◽  
Annual Precipitation ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Kurdistan Region ◽  
Oak Tree

Abstract Background The oak tree (Quercus aegilops) comprises ~ 70% of the oak forests in the Kurdistan Region of Iraq (KRI). Besides its ecological importance as the residence for various endemic and migratory species, Q. aegilops forest also has socio-economic values—for example, as fodder for livestock, building material, medicine, charcoal, and firewood. In the KRI, Q. aegilops has been degrading due to anthropogenic threats (e.g., shifting cultivation, land use/land cover changes, civil war, and inadequate forest management policy) and these threats could increase as climate changes. In the KRI and Iraq as a whole, information on current and potential future geographical distributions of Q. aegilops is minimal or not existent. The objectives of this study were to (i) predict the current and future habitat suitability distributions of the species in relation to environmental variables and future climate change scenarios (Representative Concentration Pathway (RCP) 2.6 2070 and RCP8.5 2070); and (ii) determine the most important environmental variables controlling the distribution of the species in the KRI. The objectives were achieved by using the MaxEnt (maximum entropy) algorithm, available records of Q. aegilops, and environmental variables. Results The model demonstrated that, under the RCP2.6 2070 and RCP8.5 2070 climate change scenarios, the distribution ranges of Q. aegilops would be reduced by 3.6% (1849.7 km2) and 3.16% (1627.1 km2), respectively. By contrast, the species ranges would expand by 1.5% (777.0 km2) and 1.7% (848.0 km2), respectively. The distribution of the species was mainly controlled by annual precipitation. Under future climate change scenarios, the centroid of the distribution would shift toward higher altitudes. Conclusions The results suggest (i) a significant suitable habitat range of the species will be lost in the KRI due to climate change by 2070 and (ii) the preference of the species for cooler areas (high altitude) with high annual precipitation. Conservation actions should focus on the mountainous areas (e.g., by establishment of national parks and protected areas) of the KRI as climate changes. These findings provide useful benchmarking guidance for the future investigation of the ecology of the oak forest, and the categorical current and potential habitat suitability maps can effectively be used to improve biodiversity conservation plans and management actions in the KRI and Iraq as a whole.

scholarly journals A revision of daily egg production estimation methods, with application to Atlanto-Iberian sardine. 2. Spatially and environmentally explicit estimates of egg production

2011 ◽  
Vol 68 (3) ◽  
pp. 528-536 ◽  
Author(s):  
Miguel Bernal ◽  
Yorgos Stratoudakis ◽  
Simon Wood ◽  
Leire Ibaibarriaga ◽  
Luis Valdés ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Environmental Variables ◽  
Egg Production ◽  
Stock Assessment ◽  
Production Model ◽  
Estimation Methods ◽  
Statistical Framework ◽  
Spatio Temporal ◽  
The Relationship ◽  
Made In

Abstract Bernal, M., Stratoudakis, Y., Wood, S., Ibaibarriaga, L., Uriarte, A., Valdés, L., and Borchers, D. 2011. A revision of daily egg production estimation methods, with application to Atlanto-Iberian sardine. 2. Spatially and environmentally explicit estimates of egg production. – ICES Journal of Marine Science, 68: . A spatially and environmentally explicit egg production model is developed to accommodate a number of assumptions about the relationship between egg production and mortality and associated environmental variables. The general model was tested under different assumptions for Atlanto-Iberian sardine. It provides a flexible estimator of egg production, in which a range of assumptions and hypotheses can be tested in a structured manner within a well-defined statistical framework. Application of the model to Atlanto-Iberian sardine increased the precision of the egg production time-series, and allowed improvements to be made in understanding the spatio-temporal variability in egg production, as well as implications for ecology and stock assessment.

Consistency of patterns between laboratory experiments and field collected fish in otolith chemistry: an example and applications for salinity reconstructions

2005 ◽  
Vol 56 (5) ◽  
pp. 609 ◽  
Author(s):  
T. S. Elsdon ◽  
B. M. Gillanders
Keyword(s):  
Environmental Variables ◽  
Laboratory Experiments ◽  
Juvenile Fish ◽  
Otolith Chemistry ◽  
Ambient Water ◽  
Elemental Concentrations ◽  
Adequate Knowledge ◽  
Black Bream ◽  
Environmental Histories ◽  
The Relationship

Elemental concentrations within fish otoliths can track movements and migrations of fish through gradients of environmental variables. Tracking the movements of fish relies on establishing links between environmental variables and otolith chemistry, with links commonly made using laboratory experiments that rear juvenile fish. However, laboratory experiments done on juvenile fish may not accurately reflect changes in wild fish, particularly adults. We tested the hypotheses that: (1) the relationship between ambient (water) and otolith chemistry is similar between laboratory-reared black bream (Acanthopagrus butcheri) and wild black bream; and (2) ontogeny does not influence otolith chemistry. Field-collected and laboratory-reared fish showed similar effects of ambient strontium : calcium (Sr : Ca) on otolith Sr : Ca concentrations. However, ambient and otolith barium : calcium concentrations (Ba : Ca) differed slightly between laboratory-reared and field-collected fish. Importantly, fish reared in stable environmental variables showed no influence of ontogeny on Sr : Ca or Ba : Ca concentrations. Natural distributions of ambient Sr : Ca showed no clear relationship to salinity, yet, ambient Ba : Ca was inversely related to salinity. The distribution of ambient Sr : Ca and Ba : Ca in estuaries inhabited by black bream, suggest that these elements can answer different questions regarding environmental histories of fish. Reconstructing salinity histories of black bream using otolith Ba : Ca concentrations seems plausible, if adequate knowledge of Ba : Ca gradients within estuaries is obtained.

scholarly journals Monitoring studies should consider temporal variability to reveal relations between cyanobacterial abundance and environmental variables

2015 ◽  
Vol 87 (3) ◽  
pp. 1717-1726 ◽  
Author(s):  
JULIANA WOJCIECHOWSKI ◽  
ANDRÉ A. PADIAL
Keyword(s):  
Temporal Variability ◽  
Environmental Variables ◽  
Environmental Changes ◽  
Environmental Variability ◽  
Time Lag ◽  
Cyanobacteria Blooms ◽  
Environment Variables ◽  
Sampling Points ◽  
The Relationship

One of the main goals of monitoring cyanobacteria blooms in aquatic environments is to reveal the relationship between cyanobacterial abundance and environmental variables. Studies typically correlate data that were simultaneously sampled. However, samplings occur sparsely over time and may not reveal the short-term responses of cyanobacterial abundance to environmental changes. In this study, we tested the hypothesis that stronger cyanobacteria x environment relationships in monitoring are found when the temporal variability of sampling points is incorporated in the statistical analyses. To this end, we investigated relationships between cyanobacteria and seven environmental variables that were sampled twice yearly for three years across 11 reservoirs, and data from an intensive monitoring in one of these reservoirs. Poor correlations were obtained when correlating data simultaneously sampled. In fact, the 'highly recurrent' role of phosphorus in cyanobacteria blooms is not properly observed in all sampling periods. On the other hand, the strongest correlation values for the total phosphorus x cyanobacteria relationship were observed when we used the variation of sampling points. We have also shown that environment variables better explain cyanobacteria when a time lag is considered. We conclude that, in cyanobacteria monitoring, the best approach to reveal determinants of cyanobacteria blooms is to consider environmental variability.

scholarly journals Evaluating ecological uniqueness over broad spatial extents using species distribution modelling

2021 ◽  
Author(s):  
Gabriel Dansereau ◽  
Pierre Legendre ◽  
Timothée Poisot
Keyword(s):  
North America ◽  
Species Distribution ◽  
Rare Species ◽  
Beta Diversity ◽  
Species Distribution Modelling ◽  
Distribution Models ◽  
Science Data ◽  
Distribution Modelling ◽  
Ecological Uniqueness ◽  
The Relationship

Aim: Local contributions to beta diversity (LCBD) can be used to identify sites with high ecological uniqueness and exceptional species composition within a region of interest. Yet, these indices are typically used on local or regional scales with relatively few sites, as they require information on complete community compositions difficult to acquire on larger scales. Here, we investigate how LCBD indices can be used to predict ecological uniqueness over broad spatial extents using species distribution modelling and citizen science data. Location: North America. Time period: 2000s. Major taxa studied: Parulidae. Methods: We used Bayesian additive regression trees (BARTs) to predict warbler species distributions in North America based on observations recorded in the eBird database. We then calculated LCBD indices for observed and predicted data and examined the site-wise difference using direct comparison, a spatial autocorrelation test, and generalized linear regression. We also investigated the relationship between LCBD values and species richness in different regions and at various spatial extents and the effect of the proportion of rare species on the relationship. Results: Our results showed that the relationship between richness and LCBD values varies according to the region and the spatial extent at which it is applied. It is also affected by the proportion of rare species in the community. Species distribution models provided highly correlated estimates with observed data, although spatially autocorrelated. Main conclusions: Sites identified as unique over broad spatial extents may vary according to the regional richness, total extent size, and the proportion of rare species. Species distribution modelling can be used to predict ecological uniqueness over broad spatial extents, which could help identify beta diversity hotspots and important targets for conservation purposes in unsampled locations.

scholarly journals Lowland tapir distribution and habitat loss in South America

2015 ◽  
Author(s):  
Jose Luis Passos Cordeiro ◽  
José MV Fragoso ◽  
Danielle Crawshaw ◽  
Luiz Flamarion B Oliveira
Keyword(s):  
South America ◽  
Protected Areas ◽  
Habitat Loss ◽  
Habitat Suitability ◽  
Distribution Patterns ◽  
Distribution Models ◽  
Potential Habitat ◽  
Geographical Regions ◽  
Suitability Maps ◽  
Complex Relationships

The development of species distribution models (SDMs) can help conservation efforts by generating potential distributions and identifying areas of high environmental suitability for protection. Our study presents a rigorously derived distribution and habitat map for lowland tapir in South America. We also describe the potential habitat suitability of various geographical regions and habitat loss, inside and outside of protected areas network. Two different SDM approaches, MAXENT and ENFA, produced relative different Habitat Suitability Maps for the lowland tapir. While MAXENT was efficient at identifying areas as suitable or unsuitable, it was less efficient (when compared to the results by ENFA) at identifying the gradient of habitat suitability. MAXENT is a more multifaceted technique that establishes more complex relationships between dependent and independent variables. Our results demonstrate that for at least one species, the lowland tapir, the use of a simple consensual approach (average of ENFA and MAXENT models outputs) better reflected its current distribution patterns. The Brazilian ecoregions have the highest habitat loss for the tapir. Cerrado and Atlantic Forest account for nearly half (48.19%) of the total area lost. The Amazon region contains the largest area under protection, and the most extensive remaining habitat for the tapir, but also showed high levels of habitat loss outside protected areas, which increases the importance of support for proper management.

Climate Defined but Not Soil-restricted: The Distribution of a Neotropical tree through Space and Time

2021 ◽  
Author(s):  
Facundo Alvarez ◽  
Paulo S Morandi ◽  
Ben Hur Marimon-Junior ◽  
Reginal Exavier ◽  
Igor Araújo ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Environmental Variables ◽  
Distribution Patterns ◽  
Distribution Models ◽  
Climatic Fluctuations ◽  
Space And Time ◽  
Predictive Variables ◽  
Soil Variables ◽  
Neotropical Tree ◽  
Edaphic Variables

Abstract AimsBrosimum rubescens, a tree species with a Neotropical distribution, can achieve local monodominance in Southern Amazonia forests. Understanding how and why this species varies across space and time is important because the monodominance of some species alters ecosystems complexity. Here we evaluate the fundamental ecological niche of B. rubescens by species distribution models (SDM), combining predictive environmental variables with occurrence points. We specifically aim to 1) determine how the spatial distribution patterns of B. rubescens vary with different environmental predictive variables, and 2) evaluate the temporal and spatial persistence of B. rubescens in the Neotropics. MethodsTo generate the SDMs, the predictive environmental variables were incorporated as main components of climatic, hydric and soil variables. ResultsAll algorithms show higher performance in spatial predictions for hydric variables and for the combination of climatic, hydric and edaphic variables. We identified that the potential niches of B. rubescens seem to be defined by climatic fluctuations, with the edaphic conditions being predictive variables that are not restrictive of their presence on the evaluated spatial scale. From the LMG (Last Glacial Maximum) to the present, the species seems to have increased its spatial amplitude; however, from the present to the future, predictions suggest that B. rubescens will experience a considerable loss of its range. ConclusionsOur findings show the independent and combined effects of different environmental variables, allowing us to identify which limit or facilitate the spatial distribution of B. rubescens. We corroborate the spatial persistence and geographical fidelity of the species' spatial patterns over time.

Other Techniques Related to Habitat Analysis

2021 ◽  
pp. 193-208
Author(s):  
Joseph A. Veech
Keyword(s):  
Habitat Suitability ◽  
Environmental Variables ◽  
Resource Selection ◽  
Compositional Data ◽  
Initial Step ◽  
Compositional Data Analysis ◽  
Habitat Suitability Modeling ◽  
Species Response ◽  
Habitat Analysis ◽  
Active Choice

Habitat analysis is strictly defined as a statistical examination to identify the environmental variables that a species associates with, wherein association is taken as some form of correspondence between a species response variable (e.g., presence–absence or abundance) and the environmental variables. There are other statistical techniques and empirical goals that extend this basic framework. These techniques often rely on a habitat analysis having been conducted as an initial step. Resource selection functions quantify an individual’s and a species’ use of a resource based upon the properties of the resource. Resource is broadly defined and can include particular types of habitat. Selectivity and preference indices are used to assess an individual’s preference and active choice of different resource types. Compositional data analysis is a statistical method for examining the composition of an individual’s territory or home range with regard to different habitat types that may be represented. Habitat suitability modeling and species distribution modeling are closely related techniques designed to map the spatial distribution of a species’ habitat and sometimes the species itself based upon its habitat requirements and other factors.

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